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Ingegneria Sismica

Ingegneria Sismica

Research on Mechanized Construction Technology of Transmission Line Engineering in Gobi Desert Environment

Author(s): Hao Yu1, Wenshan Ma2, Jun Zhang1, Ziyong Pan2, Jianqing Han2
1Qinghai Power Transmission and Transformation Engineering Company, Xining, Qinghai, 810001, China
2State Grid Yushu Power Supply Company, Yushu, Qinghai, 815000, China
Yu, Hao. et al “Research on Mechanized Construction Technology of Transmission Line Engineering in Gobi Desert Environment.” Ingegneria Sismica Volume 43 Issue 1: 1-23, doi:10.65102/is2026034.

Abstract

In modern society, the construction of power transmission and transformation engineering is an important foundation for promoting industrial development and improving the convenience of life, and the transmission line as the key chain of power transmission. This paper breaks down and disassembles the mechanized construction technology of transmission line project in Gobi desert environment from four aspects: apparatus entry, mechanical work, progress coordination and cost control. The improved YOLOv3 detection algorithm is proposed for the real-time detection of the entry and work of the transmission line project equipment in the Gobi desert environment to ensure the safety of the construction site. For the two aspects of schedule coordination and cost control, the constructed schedule-cost-quality balanced optimization model of transmission line project is solved by using the improved ant colony algorithm, and the entropy value-TOPSIS method is used to make decisions on the scheme. The results show that the improved YOLOv3 detection algorithm significantly improves the detection precision of engineering vehicles, and the accuracy rate can reach 88.9% and the recall rate reaches 82.8%; the improved ant colony algorithm is very suitable for multi-objective duration-cost-quality optimization, and the optimal set of solutions obtained can provide a powerful support for decision-making of the managers of transmission line construction projects.

Keywords
deep learning; target detection; ant colony algorithm; entropy value method; mechanized construction of transmission line

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